MOOC newbie voice – a slackers entrance into lak11

As LAK11 starts to ramp up (for me at least, I”m a few days behind) I thought i would take a shot at being a useful helper/facilitator for the course. My hope during this six weeks is to give a tad more guidance than i normally would in an open course and provide a safe place for discussion from people who might not know much about learning analytics, who might be new to an open course, or who are just slackers like me.

A few words on being the ombudsman
While we were talking about the roles that each of the five facilitators could take up during this course, i suggested that a voice for newbies might be useful. A person who could respond to “uh… what the xxx are they all talking about” style questions, and who could feel frustrated and confused right along with you. The simple fact is that while i’ve dabbled with LA, I’m not exactly a luminary on the subject. I’m going to be learning along with everyone else… which is why i signed on.

So feel free to ping me on witter (@davecormier) or connect with me some other way if you’re wondering what you’re supposed to be doing in this course, what a ‘hunch’ is or to complain that you can’t quite figure out what George is talking about.

I’m thinking of providing a common list of cheater options for each week, an article to skim to get a vague idea of what’s going on, a description of what i did with one of the activities and maybe some other thoughts as the week goes on. we’ll see.

Week 1 – skimming
My skimming suggestion this week is the article by Tanya Elias http://learninganalytics.net/LearningAnalyticsDefinitionsProcessesPotential.pdf. It has awesome skim potential. It’s well layed out, with titles that identify whether or not you need to read that particular part of the article. It gives you a nice background of the bits and pieces that learning analytics has grown out of and also, the potential to skip right along to the page 4 section that describes analytics… culminating with this very nice quote by dawson (also computers page 11 and theory page 14)

Although it is now accepted that a student’s social network is central for facilitating the learning process, there has been limited investigation of how networks are developed, composed, maintained and abandoned. However, we are now better placed than our predecessors to use digital technologies for the purpose of making learner networking visible…. network- poor earlier in their candidature, it becomes possible for them to make timely and strategic interventions to address this issue. (p.738)

You might very well skim this article and then decide that it’s worth the full read. ’cause it is.

This week’s activity
Hunch is pretty painless. No excuse not to be a star this week and do the activity. It gives a little window into what analytics are all about and is kinda fun to boot. I recorded myself doing it. If you just want to hang back and cheat over someone’s shoulder… be my guest.

This week’s presentation – John Fritz
It is an introduction to learning analytics. The sound is nice and clear… which is always important. It’s a nice introduction to a part of the field. Something you could easily turn on and run on your desktop while you’re working on your assignments. http://www.learninganalytics.net/?page_id=71

I found it really helpful.

It’s focused on Learning(course) Management Systems

If you’re an analytics ninja, you might want to go back to doing your weird code stuff.

Includes a use case of ‘why learning analytics’

Bottom line? Wanna sound smart at your next meeting on this topic? Watch this presentation, take notes so you can refer to the articles he talks about.

Is this useful?
If I get some sense that this is useful, I’ll do one of these every week during the course. I’ll also take feedback collected from this blog post and bring it to the friday sessions if people like?

20 thoughts on “MOOC newbie voice – a slackers entrance into lak11”

Thanks Dave, this is exactly what I needed. Work has me busy and I have a bit of time to follow along and read an article here or there. I appreciate the cheat sheet and the summary of what to expect before I check out an Elluminate presentation or read through the articles. I was 0/2 in really engaging on the first two listed on the Week 1 Syllabus. The second article was much more helpful than the first for a novice like myself but I was beginning to doubt a ‘fit’ for this course. Thanks for reeling me back in.

Hi Dave – great stuff – liked your tutorial in particular. Great way to demonstrate how simple the process is (I noticed how you gracefully by-passed the political question, after detailing your affinity for Stewart :)).

I think this gets back to some of the artifact discussions you and I have had in the past. The activity in the course each week gets to be a bit overwhelming as flow. The short presentation you did is helpful in describing elements that you found interesting…or relevant. As with the MOOC videos you did, artifacts are important in giving people a “place to point to”.

Anyway, I like where your thinking is going with this concierge/ombud role…

Thank you! This is just the sort of space I need — definitely feeling a bit overwhelmed and I have more experience in the K-12 education realm than at the university level, so that’s a bit different too. Agreed that (for my level) Tanya’s piece was the most accessible of the first three readings. Here are some ?s I had on this piece: on p.3, in the paragraph beginning with Goldstein and Katz, she contrasts academic analytics with educational data mining – I’m not following the difference. Are these really contrasting terms? Aren’t they both trying to make sense of the oceans of learner/learning related data? (Our first reading, after all, is entitled “The State of Educational Data Mining.”) Later, on p.9, she writes of the Collective Applications Model. What’s a collective application? Can you provide an example? On p. 11, in the Dawson quote, what’s an ICT? (I don’t know what other newbies think, but I would love a LAK glossary.) On p. 12, I’d be interested in a definition and more examples of digital dashboards, since that term’s come up more than once already (“performance dashoards” in the Goldstein reading). Also, a couple terminology questions from the end of the Goldstein piece — on p.11 — what are “shadow systems” And, in the Summary, what’s “ERP”? Anyhow, again, thanks, and I’m with Alan — as a Facebook hound, I Like this 🙂

Great Dave! This brings everything in an easy perspective and lowers the threshold of the perception that we need to follow everything. It immediately rings a bell for my own self-regulated learning quest.

Hi Dave, thanks for the tips.
Sorry for my disastrous English. This is my first MOOC, and it is true that the flow of information overwhelms me especially because I translate into English. On the other hand I am quickly learning the language for the account of me ;D
The truth is that I have many doubts, but I guess it will be resolved gradually as we are in the beginning. I do not know anything about Analytics, but I’m reading the texts, although I would be more involved, I think it is better to read them post for people who understand more about the subject. Thanks for being there to help.
Greetings
mercè

Thanks Dave. This is what I need. I´m here because I want to learn. I don´t have a chance to apply it anywhere so far, and part of it goes above my head. However I´m learning a lot and I´m quite happy to be here. Reading, agreeing and disagreeing, feeling confused and amazed.My neural networks are at a loss, I´m sure; creating new connections. That´s good. I´ll be around, lurking? Sorry, George.

Yes, this is useful, Very. This blog is going straight to rss reader, mooking about folder. Do not pass go. Too bad I didn’t read it before posting my “week 1 first impressions” post ~ I could have save myself a lot of time and written a much shorter post.